Optimise for post-install events to make mobile marketing more profitable

Like many things in life, mobile marketing is a marathon, not a sprint.

But too many Southeast Asian companies with mobile apps learned this the hard way. They spent millions generating installs, yet most of these installs didn’t result in usage or revenue.

Fortunately, today, Asian mobile marketers have access to more data points which, enable them to make smarter app install marketing decisions. Instead of focusing on installs, mobile marketers can instead analyse PIE or post-install events, the actions that users take after they install an app.

A focus on profitable users, and how to best acquire and recruit them

Post-install events can include user registration, usage metrics like pages viewed and time spent, levels reached, content views, making in-app purchases and buying products or services from within the app.

Then, by comparing PIE of users who generate revenue with the rest of their install base, mobile marketers are able to determine what makes a profitable user, and how best to recruit them.

For most mobile marketers, the PIE you’ll monitor will be your Key Performance Indicators (KPIs). So for an e-commerce app, you’ll focus on user acquisition costs vs. the number and size of transactions generated and the Return on Investment (ROI). And for an entertainment app, you might look at the revenue generated from the first movie streamed and how quickly this revenue was generated.

Once an app marketing team has determined the post-install events to monitor based on their analysis of higher revenue users and their PIE, the next step is to assign a value to these events. This value might be the Rupiah value of a shopping cart purchase, the number of items purchased or even the number of visits or time-spent within a given period of time. Whatever the PIE selected, they will be the ones which correlate with high revenue app usage.

For some apps, the PIE which most closely correlate with high revenue users aren’t necessarily revenue-generating events. For example, for one e-commerce app, the number of visits to the app was the PIE used by the company and not the value of products bought or even the number of items placed in the shopping cart. Therefore it’s necessary to have data scientists run the numbers to make sure that the PIE selected are really the best ones for each app. Fortunately, we have many capable and qualified data scientists in Southeast Asia to run sophisticated mobile marketing optimization utilizing PIE analysis.

What is your acquisition cost?

Once the PIE(s) and values have been determined, it’s time for the app marketers to analyse all user acquisition campaigns according to the PIE to determine the relative profitability of each source. Some sources might be delivering few users, but those users might be very profitable, while other sources might be delivering many unprofitable users. By using PIE to determine user acquisition tactics and spending, app marketers can be sure to optimize their campaigns to deliver profitable users.

As with everything in digital marketing, app marketers need to constantly test the performance of their PIEs across mobile user acquisition channels because seasonality, competition and market dynamics could change the performance of a specific PIE in some channels.

In the race for users, mobile marketing has been a little chaotic over the last few years. Now, it’s time to turn to data science in order to bring more methodology to how app marketers allocate their marketing budgets and acquire new users. Post-install events analysis is a proven method for making order out of the chaos of mobile marketing in Southeast Asia while bringing revenue-driven discipline to mobile user acquisition.

More Americans feel like people should be acting at least twice as charitably as they really do. While most of us feel like people should be giving around 6% of their annual income to charity, the typical person actually gives about half that—only 3% overall. The gap between ambition and action leaves behind a huge sum of potential donations: about $291 billion.
Nonprofit behavioral design firm Ideas42 hopes to fix that. After discovering the discrepancy through its own research in 2016, the organization began experimenting with ways to change it. The result, which was achieved with backing from the Gates Foundation, is a newly released report entitled Best of Intentions. It reads like a theoretical generosity-inspiring playbook, chronicling the findings from several experiments that have nudged people toward auditing their own behavior and then acting more altruistically.
[Source Image: Hollygraphic/iStock]
“We think there [are] ways to help people be not only more generous but more intentional and informed about their giving,” says Omar Parbhoo, a VP at Ideas42, and co-author of the report. “Because at the end of the day people want to maximize the impact they’re having, so dollars help but choosing well is also just as crucial.”
The group decided to focus not on solicitations from individual charities, many of which use their own gimmicks to drive emotional responses, but on the underlying architecture that surrounds the giving experience: platforms where people go to make donations, research charities, or view an overall summary of their contributions.
In one case, the group worked with Bright Funds, a workplace donation platform, to create a goal-setting tool and progress tracker on its giving homepage. The widget appeared six weeks before the end of the holiday season. Users could select what percentage of their income they wanted to donate and then enter an annual salary range to see the dollar amount they’d need to give, which they could then lock-in or modify. The experience included a message about what donors typically think people should give because that’s the sort of bar-setting that in other tests has been shown to nudge people toward acting more ambitiously.
[Source Image: Hollygraphic/iStock]
Whenever users visited their account page, they’d see the balance remaining to meet that goal. (At one point, the team also sent an email reminder with dollars-given and distance-to-go figures.) In a controlled test of over 18,000 total account members, the setup led to a 7% increase among donors who were already giving regularly, and nearly 18% increase among those who hadn’t started. “We really see people changing behavior when they take a broader picture of their giving,” Parbhoo says.
In another instance, Ideas42 created a different sort of score sheet, which it distributed to the clients of a large (and anonymous) donor-advised fund firm. DAFs are a type of philanthropic investment vehicle that has drawn scrutiny because donors can contribute money for an immediate tax benefit, but then wait years to distribute that money to cause groups. “We ended up sending out a year in review [email] of their activity at the end of November saying, ‘This is the amount you’ve contributed to your account, this is the amount you’ve granted out, this is the number of grants you made,” Parbhoo says. The message also alerted people that they’d get another update after the New Year, a tactic that provides a timely cue for anyone disappointed by their current habits shift that behavior shift not only before the end of the year but in advance of an impending review.
For those who received the prompt, contributions rose 12% more than for those who didn’t. Ideas42 didn’t share data on what the overall effect was on grantmaking behavior (the industry standard is that about 20% of what goes in currently gets redistributed) but among the smaller account holders there was an obviously large effect: Their contributions rose 63%, while the money they granted rose 55% compared to those who didn’t get these notifications.
Another hurdle along what Parbhoo calls the “the donor journey” is that people tend to form opinions about where to give and aren’t always open to new guidance, even if can lead to more efficient or effective contributions. In a third experiment, Ideas42 found that finding the right expert to present a short, curated list of options might change things, although the effect varies based on where who the person is and where the list gets presented.
[Source Image: Hollygraphic/iStock]
To document that, as the report notes, the group tapped Intentional Futures, a progressive consultancy, recruit top philanthropists and recognizable cause funders willing to create a so-called “GiveList” of between three to eight groups working in areas they knew well (say Ted Turner on conservation or the Gates Foundation on water sanitation and hygiene groups).
These were displayed on a couple DAF sites, a workplace giving homepage, and on the nonprofit evaluator Charity Navigator. While the results varied, ultimately folks on Charity Navigator who saw a curated list versus non-curated one ended up donating twice as much as those who didn’t. Parbhoo things the technique creates a “signal of quality” that allows people to put aside fears that their money might be wasted and perhaps want to give even more.
None of these tweaks is meant to block people’s inclination to give immediately to something urgent that arises, say a natural disaster or unexpected tragic event. “What we’re trying to do here is be something that is additive and complementary, so please give when your heartstrings are tugged, but also make sure that you are thinking through what outcomes you want to reach in your philanthropy and ensure that you’re doing that as well,” he says.
Parbhoo hopes that eventually the act of giving more and more mindfully might generate the sort of positive results that can be its own incentive, but there’s still a lot more to learn. “At the moment, we’re still focusing on closing that gap.”

If you’re using an Android phone or have Google apps installed on your iPhone, the search giant is almost certainly tracking your location constantly – even if you’ve turned that setting off, reports the Associated Press. The story drew from UC Berkeley graduate researcher K. Shankari’s experience of her Android device keeping tabs on her movements while she had Location History turned off. Blogging back in May, she said that at one point, Google prompted her to rate a shopping trip to Kohl’s – something the company could only have known about by tracking her location. The AP then traced… This story continues at The Next WebOr just read more coverage about: Google